Article

Computer aided fuzzy medical diagnosis

Centre for Computational Intelligence, Department of Computer Science, De Montfort University, The Gateway, Leicester LE1 9BH, UK
Information Sciences DOI:10.1016/j.ins.2004.03.003 pp.81-104

ABSTRACT This paper describes a fuzzy approach to computer aided medical diagnosis in a clinical context. It introduces a formal view of diagnosis in clinical settings and shows the relevance and possible uses of fuzzy cognitive maps and fuzzy logic. A constraint satisfaction method is introduced which uses the temporal uncertainty in symptom durations that may occur with particular diseases. Together with fuzzy symptom descriptions, the method results in an estimate of the stage of a disease if the temporal constraints of the disease in relation to the occurrence of the symptoms are satisfied. The approach is evaluated through simulation experiments showing the effects of symptom ordering, temporal uncertainty and symptom strengths on the diagnosis efficiency. The method is effective and can be developed further using second order (Type 2) fuzzy logic to better represent uncertainty in the clinical context thus improving differential diagnosis accuracy.

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Keywords

clinical context
 
clinical settings
 
constraint satisfaction method
 
diagnosis efficiency
 
differential diagnosis accuracy
 
formal view
 
fuzzy approach
 
fuzzy cognitive maps
 
fuzzy symptom descriptions
 
medical diagnosis
 
method results
 
particular diseases
 
second order
 
symptom durations
 
symptom strengths
 
symptoms
 
temporal constraints
 
temporal uncertainty
 

P.R. Innocent